TY - GEN
T1 - Ant colony algorithm used for bankruptcy prediction
AU - Wang, Shuihua
AU - Wu, Lenan
AU - Zhang, Yudong
AU - Zhou, Zhengyu
PY - 2009
Y1 - 2009
N2 - Bankruptcy prediction is a hot topic. Traditional methods consist of univariate model and multivariate model such as neural network. However, the NNs can not extract effective rules. Thus, a novel approach was proposed in this paper to extract rules. First, t-test method was used to select 5 features from 55 original features. Second, the rule encoding was constructed. Third, the ant colony algorithm was utilized to find the optimal rule. Experiments on 200 corporate demonstrate that this proposed algorithm is effective and rapid.
AB - Bankruptcy prediction is a hot topic. Traditional methods consist of univariate model and multivariate model such as neural network. However, the NNs can not extract effective rules. Thus, a novel approach was proposed in this paper to extract rules. First, t-test method was used to select 5 features from 55 original features. Second, the rule encoding was constructed. Third, the ant colony algorithm was utilized to find the optimal rule. Experiments on 200 corporate demonstrate that this proposed algorithm is effective and rapid.
KW - Ant colony optimization
KW - Bankruptcy prediction
UR - http://www.scopus.com/inward/record.url?scp=77952662051&partnerID=8YFLogxK
U2 - 10.1109/ISISE.2009.11
DO - 10.1109/ISISE.2009.11
M3 - Conference Proceeding
AN - SCOPUS:77952662051
SN - 9780769539911
T3 - 2nd International Symposium on Information Science and Engineering, ISISE 2009
SP - 137
EP - 139
BT - 2nd International Symposium on Information Science and Engineering, ISISE 2009
PB - IEEE Computer Society
T2 - 2009 2nd International Symposium on Information Science and Engineering, ISISE 2009
Y2 - 26 December 2009 through 28 December 2009
ER -